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兵工学报 ›› 2019, Vol. 40 ›› Issue (6): 1171-1178.doi: 10.3969/j.issn.1000-1093.2019.06.007

• 论文 • 上一篇    下一篇

前视红外图像中海岸线与海天线的通用检测方法研究

仇荣超1, 吕俊伟1, 宫剑1, 修炳楠1, 马新星1, 刘思彤2   

  1. (1.海军航空大学, 山东 烟台 264001; 2.空军西安飞行学院 空中特种勤务系, 陕西 西安 710300)
  • 收稿日期:2018-08-29 修回日期:2018-08-29 上线日期:2019-08-14
  • 作者简介:仇荣超(1990—), 男, 博士研究生。 E-mail: qrc_smile@sina.com
  • 基金资助:
    武器装备“十三五”预先研究项目(2016年)

Research on General Detection Method of Coastline and Sea-sky Line in FLIR Image

QIU Rongchao1, L Junwei1, GONG Jian1, XIU Bingnan1, MA Xinxing1, LIU Sitong2   

  1. (1. Naval Aviation University, Yantai 264001, Shandong, China;2. Special Service Department, Xi'an Flight Academy of Air Force, Xi'an 710300, Shaanxi, China)
  • Received:2018-08-29 Revised:2018-08-29 Online:2019-08-14

摘要: 海岸线与海天线检测作为前视红外成像型反舰导弹末制导技术中的关键技术,通常会受到岛岸、云层、亮带、条状波浪等多种因素干扰。为解决这一问题,提出了一种海岸线与海天线的通用检测方法。对原始图像构建积分图像,采用箱式滤波器来增强海岸线与海天线的边缘特征;逐行滑动统计矩形区域内像素的梯度显著性来确定海岸线与海天线潜在区域,通过潜在区域内逐列寻找显著性最大值点,并对所有的最大值点进行多项式迭代拟合,获得海岸线与海天线的准确位置;基于实际采集的前视红外海面场景图像对该方法进行了验证和分析。结果表明,通用检测方法能够克服岛岸、云层、亮带、条状波浪等复杂背景的干扰,实现海岸线与海天线的检测,场景适应性强,实时性好。

关键词: 前视红外图像, 海岸线, 海天线, 梯度显著性, 多项式迭代拟合

Abstract: The coastline and sea-sky line detection is a key technology in the forward looking infrared (FLIR) terminal guidance technology of anti-ship missile, which is always interfered by island, cloud, bright band, strip wave and so on. A general detection method for coastline and sea-sky line is proposed. An integral image is constructed for the original image, and the box filter is used to enhance the edge features of coastline and sea-sky line. The gradient saliency of the pixels in the rectangular region is counted to determine the potential area of the coastline and sea-sky line. The points with maximum saliency are extracted in each column of the potential area and are used to obtain the locations of coastline and sea-sky line by polynomial iterative fitting. The proposed method is verified and analyzed based on the actual FLIR images of sea scene. The results show that the proposed method can overcome the interference of island, cloud, bright band, and strip wave to detect the coastline and sea-sky line. The proposed method has good scene adaptability and real-time performance. Key

Key words: forwardlookinginfraredimage, coastline, sea-skyline, gradientsaliency, polynomialiterativefitting

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